U.S. patent number 8,666,309 [Application Number 12/864,609] was granted by the patent office on 2014-03-04 for system for distributed beamforming for a communication system employing relay nodes.
This patent grant is currently assigned to Nokia Corporation. The grantee listed for this patent is Peter Fertl, Ari Hottinen. Invention is credited to Peter Fertl, Ari Hottinen.
United States Patent |
8,666,309 |
Hottinen , et al. |
March 4, 2014 |
System for distributed beamforming for a communication system
employing relay nodes
Abstract
In accordance with aspects of the present invention, a method,
apparatus and system for learning antenna weighting factors in a
communication system including relay nodes. In one embodiment, an
apparatus (e.g., a relay node (325)) for use with a communication
system includes a first antenna (330) configured to receive a first
signal including a pilot training sequence from a source node (305)
and a second signal including a power-based feedback signal or a
signal-to-noise based feedback signal from a destination node
(350). The apparatus also includes a second antenna (335)
configured to transmit at least a portion of the first signal with
an antenna weighting factor (e.g., a perturbed antenna weighting
factor). The apparatus further includes an antenna weighting factor
module (340) coupled to the first antenna (330) and configured to
iteratively adjust the antenna weighting factor in response to the
second signal.
Inventors: |
Hottinen; Ari (Espoo,
FI), Fertl; Peter (Vienna, AT) |
Applicant: |
Name |
City |
State |
Country |
Type |
Hottinen; Ari
Fertl; Peter |
Espoo
Vienna |
N/A
N/A |
FI
AT |
|
|
Assignee: |
Nokia Corporation (Espoo,
FI)
|
Family
ID: |
39885710 |
Appl.
No.: |
12/864,609 |
Filed: |
January 28, 2008 |
PCT
Filed: |
January 28, 2008 |
PCT No.: |
PCT/IB2008/050301 |
371(c)(1),(2),(4) Date: |
July 26, 2010 |
PCT
Pub. No.: |
WO2009/095744 |
PCT
Pub. Date: |
August 06, 2009 |
Prior Publication Data
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|
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Document
Identifier |
Publication Date |
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US 20100304666 A1 |
Dec 2, 2010 |
|
Current U.S.
Class: |
455/7; 455/13.1;
455/11.1; 455/69; 370/315 |
Current CPC
Class: |
H04B
7/155 (20130101); H04B 7/026 (20130101); H04B
7/0619 (20130101); H04B 7/022 (20130101); H04B
7/0417 (20130101) |
Current International
Class: |
H04B
7/14 (20060101) |
Field of
Search: |
;455/7,13.1,13.4,69,522,509,562.1,500,553.1,132,101,133,24,11.1,25,9,67.11,561,63.4,272,276.1
;370/315,316,318,329,482 ;375/267 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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1638236 |
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Mar 2006 |
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EP |
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2006088400 |
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Aug 2006 |
|
WO |
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Other References
Bolcskei et al., "Capacity scaling laws in MIMO relay networks",
IEEE Trans. Wireless Comm., vol. 5, pp. 1433-1444, Jun. 2006. cited
by applicant .
Morgenshtern et al., "Crystallization in large wireless networks."
IEEE Trans. on Information Theory, vol. 53, No. 10, Oct. 2007.
cited by applicant .
Banister et al., "Feedback assisted stochastic gradient adaptation
of multiantenna transmission," IEEE Trans. Wireless Comm., vol. 4,
pp. 1121-1135, May 2005. cited by applicant .
Raghothaman, "Deterministic perturbation gradient approximation for
transmission subspace tracking in FDD-CDMA," in Proc. IEEE
ICC-2003, vol. 4, pp. 2450-2454, May 2003. cited by applicant .
Nguyen et al., "Quantized-feedback optimal adaptive beamforming for
FDD systems," in Proc. IEEE ICC-2006, vol. 9, pp. 4202-4207, Jun.
2006. cited by applicant .
Mudumbai et al., "Distributed transmit beamforming using feedback
control," Arxiv preprint cs.IT/0603072, Mar. 2006. cited by
applicant .
Mudumbai, "On the feasability of distributed beamforming in
wireless networks," IEEE Trans. Wireless Comm., vol. 6, pp. 1-10,
Apr. 2007. cited by applicant .
International Search Report and Written Opinion of the
International Searching Authority received from PCT Application No.
PCT/IB2008/050301, dated Nov. 18, 2008, 15 pages. cited by
applicant .
Fan et al., "MIMO Configurations for Relay Channels: Theory and
Practice" IEEE Transactions on Wireless Communications, IEEE
Service Center, New Jersey, vol. 6, No. 5, May 1, 2007, pp.
1774-1786. cited by applicant .
Larsson, Peter, et al., "Large-Scale Cooperative Relaying Network
with Optimal Coherent Combining under Aggregate Relay Power
Constraints", Proc. Future Telecommunication Conference (FTC),
2003, 5 pgs. cited by applicant.
|
Primary Examiner: Trinh; Tan
Attorney, Agent or Firm: Harrington & Smith
Claims
What is claimed is:
1. An apparatus, comprising: at least one processor; and at least
one memory including computer program code, where the at least one
memory and the computer program code are configured, with the at
least one processor, to cause the apparatus to at least: receive,
with a first antenna, a first signal from a source node and a
second signal from a destination node, wherein said second signal
comprises one of a power-based feedback signal and a
signal-to-noise based feedback signal from said destination node;
transmit, with a second antenna, at least a portion of said first
signal with an antenna weighting factor; and adjust said antenna
weighting factor based on at least said second signal.
2. The apparatus as recited in claim 1 wherein said second antenna
is configured to transmit at least a portion of said first signal
with a perturbed antenna weighting factor.
3. The apparatus as recited in claim 1 wherein said at least one
memory including the computer program code is configured with the
at least one processor to cause the apparatus to adjust said
antenna weighting factor with a deterministic perturbation selected
from an orthogonal vector set.
4. The apparatus as recited in claim 1 wherein said power-based
feedback signal is based on a difference of powers obtained with
more than one perturbed antenna weight at said destination
node.
5. The apparatus as recited in claim 1 wherein said at least one
memory including the computer program code is configured with the
at least one processor to cause the apparatus to iteratively adjust
said antenna weighting factor over a sequence of adjustment
steps.
6. The apparatus as recited in claim 1 wherein said first and
second antennas are antenna elements of a single antenna.
7. The apparatus as recited in claim 1 wherein said first signal
includes a pilot training sequence.
8. The apparatus as recited in claim 1 wherein said apparatus is a
relay node of said communication system.
9. The apparatus as recited in claim 1 comprising a transmitter and
receiver coupled to said first and second antennas.
10. A method, comprising: receiving, with a communication node, a
first signal from a source node and a second signal from a
destination node, wherein said second signal comprises one of a
power-based feedback signal and a signal-to-noise based feedback
signal from said destination node; transmitting, with the
communication node, at least a portion of said first signal with an
antenna weighting factor; and adjusting, with the communication
node, said antenna weighting factor based on at least said second
signal.
11. The method as recited in claim 10 wherein said transmitting
includes transmitting at least a portion of said first signal with
a perturbed antenna weighting factor.
12. The method as recited in claim 10 wherein said adjusting
includes adjusting said antenna weighting factor with a
deterministic perturbation selected from an orthogonal vector
set.
13. The method as recited in claim 10 wherein said power-based
feedback signal is based on a difference of powers obtained with
more than one perturbed antenna weight at said destination
node.
14. The method as recited in claim 10 wherein said adjusting
includes iteratively adjusting said antenna weighting factor over a
sequence of adjustment steps.
15. The method as recited in claim 10 wherein said receiving and
transmitting are performed in accordance with first and second
antennas.
16. The method as recited in claim 10 wherein said receiving and
transmitting are performed in accordance with a transmitter and
receiver of a communication node.
17. An apparatus, comprising: at least one processor; and at least
one memory including computer program code, where the at least one
memory and the computer program code are configured, with the at
least one processor, to cause the apparatus to at least: receive a
signal from one of a first and a second communication node; and
transmit a feedback signal to at least one of said first and said
second communication node to adjust an antenna weighting factor of
an antenna thereof, wherein said feedback signal comprises one of a
power-based feedback signal and a signal-to-noise based feedback
signal.
18. The apparatus as recited in claim 17 wherein said at least one
memory including the computer program code is configured with the
at least one processor to cause the apparatus to transmit said
feedback signal to said first communication node and another
feedback signal to said second communication node.
19. The apparatus as recited in claim 17 wherein said power-based
feedback signal is based on a difference of powers obtained with
more than one perturbed antenna weight.
20. A communication system, comprising: a source node configured to
transmit a first signal including a pilot training sequence; a
destination node configured to transmit a second signal; and a
relay node, including: a first antenna coupled to a receiver
configured to receive said first signal and said second signal,
wherein said second signal comprises one of a power-based feedback
signal and a signal-to-noise based feedback signal from said
destination node, a second antenna coupled to a transmitter
configured to transmit at least a portion of said first signal with
an antenna weighting factor, and an antenna weighting factor module
coupled to said first antenna and configured to adjust said antenna
weighting factor based on at least said second signal.
Description
RELATED APPLICATION
This application was originally filed as PCT Application No.
PCT/IB2008/050301 on Jan. 28, 2008, which is incorporated herein by
reference in its entirety.
TECHNICAL FIELD
The present invention is directed, in general, to communication
systems and, more particularly, to a method, apparatus and system
for learning antenna weighting factors in a communication system
including relay nodes.
BACKGROUND
The communication of information is a necessity of modern society,
which is enabled through the operation of a communication system.
Information is communicated between a sending station and a
receiving station by way of a communication channel. The sending
station, if necessary, converts the information into a form for
communication over the communication channel. The receiving station
detects and recovers the information for the benefit of a user. A
wide variety of different types of communication systems have been
developed and are regularly employed to effectuate communication
between sending and receiving stations.
An exemplary communication system is a cellular communication
system in which a communication channel is defined upon a radio
link extending between sending and receiving stations. Cellular
radio communication systems are amenable to implementation as
mobile communication systems wherein radio links, rather than
fixed, wireline connections, are employed to define communication
channels.
Generally, a cellular communication system includes a network
infrastructure that includes a plurality of base stations that are
positioned at spaced-apart locations throughout a geographic area.
Each of the base stations defines an area, referred to as a cell,
from which the cellular communication system derives its name. The
network infrastructure, of which the base stations form portions
thereof, is coupled to a core network such as a packet data
backbone or a public-switched telephone network. Communication
devices such as computer servers, telephone stations, etc., are, in
turn, coupled to the core network and are capable of communication
by way of the network infrastructure and the core network. Portable
transceivers, commonly referred to as mobile stations, communicate
with the base stations by way of such radio links.
Information communicated over a radio link is susceptible to
imperfect communication such as distortion resulting from nonideal
communication conditions. Distortion causes the information
delivered to a receiving station to differ from the corresponding
information transmitted by the sending station. If the distortion
is significant, the informational content cannot be accurately
recovered at the receiving station. For instance, fading caused by
multi-path transmission distorts information communicated over a
communication channel. If the communication channel exhibits
significant levels of fading, the informational content may not be
recoverable.
Various techniques such as spatial diversity are employed to
compensate for or otherwise overcome distortion introduced upon the
information transmitted over a communication channel to a receiving
station. Spatial diversity is typically created through the use at
a sending station of more than one transmit antenna from which
information is transmitted, thereby creating spatial redundancy
therefrom. The antennas are typically separated by distances
sufficient to ensure that the information communicated by
respective antennas fades in a sufficiently uncorrelated manner.
Additionally, a receiving station can sometimes use more than one
receiving antenna, preferably separated by appropriate
distances.
Communication systems that utilize both multiple transmitting
antennas and multiple receiving antennas are often referred to as
being multiple-input, multiple-output ("MIMO") systems.
Communications in a MIMO system provide the possibility that higher
overall communication performance of the system, relative to a
conventional system, can be achieved. As a result, an increased
number of users may be serviced or more data throughput may be
provided with improved reliability for each user. The advantages
provided through the use of spatial diversity are further enhanced
if the sending station is provided with information about the state
or performance of the communication channel between the sending and
receiving stations.
In multiple antenna systems, an approach to increase the strength
of a desired signal at the receiver is to make use of transmit
beamforming. By coherently combining the signal transmitted from
multiple transmit antennas, the signal-to-noise ratio ("SNR") at
the receiver of a transceiver can be increased, which leads to
significant performance gains. Moreover, this approach also
provides communication benefits by exploiting transmit diversity.
However, this usually requires knowledge of channel state
information ("CSI") at the transmitter of a transceiver, which
implies a high level of signaling/feedback overhead. The amount of
feedback can be reduced by applying antenna weighting factors at
the transmitter, and updating the antenna weighting factors using
only limited feedback from the receiver. The feedback signal can be
generated by perturbing the antenna weighting factors and
estimating the impact of the perturbation at the receiver (e.g., by
estimating the received signal power). The influence of the
perturbation is then reflected in the feedback signal. This
approach (which is also referred to as "subspace tracking") allows
adaptive antenna weighting factor learning, and closely converges
to the performance gains achieved by coherent received signal
combining.
A sending station generally cannot measure channel characteristics
of the communication channel directly, such as a channel
correlation matrix representing a product of channel impulse
response components for the multiple transmitting antennas. Thus, a
receiving station typically measures the characteristics of the
communication channel. In two-way communication systems,
measurements made at a receiving station can be returned to the
sending station to provide channel characteristics to the sending
station. Communication systems that provide this type of
information to multiple-antenna sending stations are referred to as
closed-loop transmit diversity systems.
The feedback signal returned to the sending station (e.g., a base
station) from the receiving station (e.g., a mobile station) is
used to select or refine values of antenna weighting factors. The
antenna weighting factors are values including amplitude and phase
by which information signals coupled to individual antennas are
weighted prior to their transmission over a communication channel
to the mobile station. A goal is to weight the information signals
applied to the antennas in amplitude and phase in a manner that
best facilitates communication of the information to the receiving
station. Estimation of the antenna weighting factors can be
formulated as a transmission subspace tracking procedure. Several
closed-loop transmit diversity procedures may be utilized.
A technique to improve reliability of communication between a
sending station and a receiving station is to employ relay nodes
("RNs"), which may be fixed or mobile communication nodes that act
as signaling relays to improve the reception of a weak or corrupted
signal at a destination node. A relay node forwards a message from
a source node ("SN"), which is a node that needs assistance from a
relay node, to a destination node ("DN"), which is the node that
finally receives the message that may be weak or otherwise
corrupted. In general, the aforementioned communication devices
(e.g., SN, DN, or RN) form wireless nodes.
In a system employing relay nodes, in a simple but illuminating
example, the problem can be translated into coherently combining
desired signals at the relay nodes. This is done by co-phasing the
received signals with respect to the backward channel (e.g., the
source-relay channel) and the forward channel (e.g., the
relay-destination channel) as described by H. Bolcskei, et al., in
the paper entitled "Capacity Scaling Laws in MIMO Relay Networks,"
IEEE Trans. Wireless Comm., Vol. 5, No. 6, pp. 1433-1444, June
2006, which is incorporated herein by reference. However,
implementation of such a system to adjust antenna weighting factors
requires feedback of the full CSI of the forward channel from the
destination node to the relay nodes, which is clearly
inefficient.
Several weighted transmission methods for a plurality of antennas
have been studied in the past. However, efforts in this area have
focused mainly on centralized antenna arrays, without the use of
intervening relay nodes. In the paper by B. C. Banister, et al.,
entitled "Feedback Assisted Stochastic Gradient Adaptation of
Multiantenna Transmission," IEEE Trans. Wireless Comm., Vol. 4, No.
3, pp. 1121-1135, May 2005, and in U.S. Pat. No. 6,952,455,
entitled "Adaptive Antenna Method and Apparatus," by Bannister,
Oct. 4, 2005, which are incorporated herein by reference, an
iterative algorithm using one-bit feedback was described that uses
random vector perturbations to achieve desired beamforming gains.
In the paper by B. Raghothaman, entitled "Deterministic
Perturbation Gradient Approximation for Transmission Subspace
Tracking in FDD-CDMA," Proc. IEEE ICC-2003, Vol. 4, pp. 2450-2454,
May 2003, and in U.S. Pat. No. 6,842,632, entitled "Apparatus, and
Associated Method, for Facilitating Antenna Weight Selection
Utilizing Deterministic Perturbation Gradient Approximation," by B.
Raghothaman and R. T. Derryberry, Jan. 11, 2005, which are
incorporated herein by reference, a similar approach utilizes a
deterministic set of perturbation vectors. Both approaches are
based on an adaptive gradient search technique and assume
centralized antenna arrays, where the transmission weights are
modified in the source transceiver.
As described in the paper by H. Nguyen and B. Raghothaman, entitled
"Quantized-Feedback Optimal Adaptive Beamforming for FDD systems,"
Proc. IEEE ICC-2006, Vol. 9, pp. 4202-4207, June 2006, which is
incorporated herein by reference, the adaption rate of antenna
weighting factors can be influenced by changing the amount of
feedback (i.e., the number of feedback bits). Recently, beamforming
algorithms for distributed transmitters have been investigated as
described by R. Mudumbai, et al., in the paper entitled
"Distributed Transmit Beamforming Using Feedback Control," Arxiv
preprint cs.IT/0603072, 2006, which is incorporated herein by
reference. In the aforementioned paper, a virtual antenna array of
sensors coherently transmits a common message to a base station. It
is shown that coherent transmission can be achieved asymptotically
by random phase perturbations at distributed transmitters. However,
a relay arrangement including a relay node was not considered. In
the above reference, the pilot signals are transmitted from the
same spatial location where updating of antenna weighting factors
is applied.
Considering the limitations as described above, a system and method
to control antenna weighting factors for beamforming with multiple
antennas employed in a wireless communication system including at
least one source node, at least one relay node, and at least one
destination node is not presently available. Accordingly, what is
needed in the art is a system that learns real or complex antenna
weighting factors for at least a subset of relay node antennas,
preferably using low-rate feedback, overcoming many of the
aforementioned limitations. In accordance therewith, a beamforming
arrangement for multiple antennas in a communication system
employing at least one source node, at least one relay node, and at
least one destination node, that generates antenna weighting
factors for beamforming of multiple relay node antennas would
provide improved reliability of communication in a communication
system.
SUMMARY OF THE INVENTION
These and other problems are generally solved or circumvented, and
technical advantages are generally achieved, by embodiments of the
present invention, which include a method, apparatus and system for
learning antenna weighting factors in a communication system
including relay nodes. In one embodiment, an apparatus (e.g., a
relay node) for use with a communication system includes a first
antenna configured to receive a first signal including a pilot
training sequence from a source node and a second signal including
a power-based feedback signal or a signal-to-noise based feedback
signal from a destination node. The apparatus also includes a
second antenna configured to transmit or relay at least a portion
of the first signal with an antenna weighting factor (e.g., a
perturbed antenna weighting factor). The first and second antennas
may be antenna elements of a single antenna. The apparatus further
includes an antenna weighting factor module coupled to the first
antenna and configured to adjust the antenna weighting factor with
a deterministic perturbation selected from an orthogonal vector set
in response to the second signal. The antenna weighting factor
module may also be configured to adjust the antenna weighting
factor with a perturbation generated from a random Gaussian vector
in response to the second signal. The antenna weighting factor
module may iteratively adjust the antenna weighting factor over a
sequence of adjustment steps. The apparatus still further includes
a transmitter and receiver coupled to the first and second
antennas.
In another aspect, an apparatus for use with a communication system
includes means for receiving a first signal including a pilot
training sequence from a source node and a second signal including
a power-based feedback signal or a signal-to-noise based feedback
signal from a destination node. The apparatus also includes means
for transmitting at least a portion of the first signal with an
antenna weighting factor. The apparatus further includes means for
iteratively adjusting the antenna weighting factor with a
deterministic perturbation over a sequence of adjustment steps in
response to the second signal.
In another aspect, a method of operating a communication node
includes receiving a first signal including a pilot training
sequence from a source node and a second signal including a
power-based feedback signal or a signal-to-noise based feedback
signal from a destination node. The method also includes
transmitting at least a portion of the first signal with a
perturbed antenna weighting factor. The method further includes
iteratively adjusting the antenna weighting factor with a
deterministic perturbation selected from an orthogonal vector set
over a sequence of adjustment steps in response to the second
signal. The antenna weighting factor may also be adjusted with a
perturbation generated from a random Gaussian vector in response to
the second signal.
In another aspect, an apparatus for use with a communication system
includes an antenna configured to receive a signal from first and
second communication nodes and a feedback generator configured to
transmit a feedback signal (e.g., a power-based feedback signal or
a signal-to-noise based feedback signal) to at least one of the
first and second communication nodes to adjust an antenna weighting
factor of an antenna thereof. The apparatus may be a destination
node and at least one of the first and second communication nodes
may be relay nodes. The feedback generator may be configured to
transmit the feedback signal to the first communication node and
another feedback signal to the second communication node. In a
related aspect, a method, a computer program product and means for
performing the aforementioned functions are also provided
herein.
In another aspect, a communication system includes a source node
configured to transmit a first signal including a pilot training
sequence and a destination node configured to transmit a second
signal including a power-based feedback signal or a signal-to-noise
based feedback signal. The communication system also includes a
relay node (e.g., a mobile station) having a first antenna
configured to receive the first signal and the second signal. The
relay node also includes a second antenna configured to transmit at
least a portion of the first signal with a perturbed antenna
weighting factor. The relay node further includes an antenna
weighting factor module coupled to the first antenna and configured
to iteratively adjust the antenna weighting factor with a
deterministic perturbation selected from an orthogonal vector set
over a sequence of adjustment steps in response to the second
signal. The antenna weighting factor module may also be configured
to adjust the antenna weighting factor with a perturbation
generated from a random Gaussian vector in response to the second
signal. The relay node still further includes a transmitter and
receiver coupled to the first and second antennas.
The foregoing has outlined rather broadly the features and
technical advantages of the present invention in order that the
detailed description of the invention that follows may be better
understood. Additional features and advantages of the invention
will be described hereinafter which form the subject of the claims
of the invention. It should be appreciated by those skilled in the
art that the conception and specific embodiment disclosed may be
readily utilized as a basis for modifying or designing other
structures or processes for carrying out the same purposes of the
present invention. It should also be realized by those skilled in
the art that such equivalent constructions do not depart from the
spirit and scope of the invention as set forth in the appended
claims.
BRIEF DESCRIPTION OF THE DRAWINGS
For a more complete understanding of the invention, and the
advantages thereof, reference is now made to the following
descriptions taken in conjunction with the accompanying drawing, in
which:
FIG. 1 illustrates a block diagram of an embodiment of a
communication system that provides radio communication between
communication stations via communication channels employing an
exemplary beamforming arrangement that includes a deterministic
perturbation gradient approximation to adjust antenna weighting
factors;
FIG. 2 illustrates a system level diagram of a wireless
communications system including a source node with one or more
antennas controlled by antenna weighting factors, and a destination
node providing feedback to adjust the antenna weighting
factors;
FIG. 3 illustrates a system level diagram of a wireless
communication system including a source node, a relay node with
antennas controlled by antenna weighting factors, and a destination
node providing feedback to adjust the antenna weighting
factors;
FIG. 4 illustrates a graph demonstrating that enhanced power
allocation can be achieved using a learning weights method;
FIG. 5 illustrates a flow diagram demonstrating steps that may be
performed in the operation of a communication system including a
source node, one or more relay nodes with antennas controlled by
antenna weighting factors, and a destination node providing
feedback to adjust the antenna weighting factors;
FIG. 6 illustrates a graph showing bit-error rate versus
signal-to-noise ratio for a one-bit deterministic feedback
antenna-weighting-factor learning scheme; and
FIG. 7 illustrates a graph of convergence behavior of a one-bit
deterministic feedback scheme to adjust antenna weighting factors
with five relay nodes.
DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS
The making and using of the presently preferred embodiments are
discussed in detail below. It should be appreciated, however, that
the present invention provides many applicable inventive concepts
that can be embodied in a wide variety of specific contexts. The
specific embodiments discussed are merely illustrative of specific
ways to make and use the invention, and do not limit the scope of
the invention.
The present invention will be described with respect to exemplary
embodiments in a specific context of beamforming with multiple
antennas in a wireless communication system including a source
node, one or more relay nodes, and a destination node. In general,
embodiments of the invention may be applied to any form of
communication system and network such as a cellular wireless
communication system and network. For additional information about
beamforming systems, see a paper by V. I. Morgenshtern, et al.,
entitled "Crystallization in Large Wireless Networks," IEEE Trans.
on Information Theory, Vol. 53, Iss. 10, October 2007, pp.
3319-3349, and U.S. Pat. No. 7,224,758, entitled "Multiple Transmit
Antenna Weighting Techniques," by Bannister, May 29, 2007, and U.S.
Patent Application Publication No. 2007/0191067, entitled "Adaptive
Beamforming Systems and Methods for Communication Systems," by H.
Nguyen and B. Raghothaman, Aug. 16, 2007, and a paper by R.
Mudumbai, et al., entitled "On the Feasability of Distributed
Beamforming in Wireless Networks," IEEE Trans. Wireless Comm., Vol.
6, No. 4, pp. 1-10, April 2007, which are incorporated herein by
reference.
Referring now to FIG. 1, illustrated is a block diagram of an
embodiment of a communication system that provides radio
communication between communication stations via communication
channels employing an exemplary beamforming arrangement that
includes a deterministic perturbation gradient approximation to
adjust antenna weighting factors. The communication system includes
a base station 100 as a source node and a mobile station 170 as a
destination node. The communication channels are defined by radio
links such as forward channel 105 and backward channel 110.
Information sent to the mobile station 170 is communicated by the
base station 100 over the forward channel 105 and information
originated at the mobile station 170 for communication to the base
station 100 is communicated over backward channel 110. The
communication system may be a cellular communication system
constructed pursuant to any of a number of different cellular
communication standards. For instance, the base station and mobile
station may be operable in a code division multiple access ("CDMA")
communication system such as a third generation ("3G") CDMA
communication.
The base station 100 forms part of a radio access network that also
includes a radio network controller 115 coupled to a gateway 120
and a mobile switching center 125. The gateway 120 is coupled to a
packet data network ("PDN") 130 such as the Internet, and the
mobile switching center 125 is coupled to a public switched
telephone network ("PSTN") 135. A correspondent node 137 is coupled
to the packet data network 130 and to the PSTN 135. The
correspondent node 137 represents a data source or a data
destination from which, or to which, information is routed during
operation of the communication system.
The base station 100 includes a receiver 140 and a transmitter 145.
A forward-channel signal to be communicated by the base station 100
to the mobile station 170 is converted into a format for
communication over the forward channel 105 by the transmitter 145.
Closed-loop feedback information is returned by the mobile station
170 to the base station 100 by way of the backward channel 110. The
mobile station 170 also includes a receiver 175 and a transmitter
180. The receiver 175 operates to receive, and operate upon, the
forward-channel signals transmitted by the base station 100 over
the forward channel 105, and the transmitter 180 operates to
transmit backward-channel signals over the backward channel 110 to
the base station 100.
The base station 100 and the mobile station 170 include multiple
antennas, and the base station 100 and the mobile station 170
combination forms a multiple-input, multiple-output ("MIMO")
system. For purposes of clarity, the base station 100 includes R
base station antennas designated 147-1 to 147-R (hereinafter
referenced as base station antennas 147). Also for purposes of
clarity, the mobile station 170 includes N mobile station antennas
designated 185-1 to 185-N (hereinafter referenced as mobile station
antennas 185).
The base station transmitter 145 includes an encoder 150 that
encodes data to form encoded data. The encoded data is provided to
an up-mixer 155 with an up-mixing carrier v(t) to generate an
up-mixed signal. The up-mixed signal is provided via antenna
weighting elements (two of which are referenced and designated as
first and second antenna weighting elements 160, 162, respectively)
on separate branches to ones of the base station antennas 147. Once
the up-mixed signals are weighted, the weighted signals are applied
to the base station antennas 147 for transmission to the mobile
station 170. Of course, other operations may be performed on the
weighted signals prior to transmission to the mobile station 170.
The base station transmitter 145 may also include a pilot signal
source to generate a pilot training sequence to be transmitted wth
the weighted signals.
The base station 100 also includes a deterministic perturbation
gradient approximation system as an exemplary process to adjust the
values of the antenna weightings applied to the first and second
antenna weighting elements 160, 162 in a manner that enhances
antenna weighting factor selection pursuant to a closed-loop
transmit diversity system. The deterministic perturbation gradient
approximation system (which may be embodied in hardware, software,
or combinations thereof) includes a perturbation vector selector
("PVS") 165 that operates to select perturbation vectors formed of
vector values (indicating a perturbed amplitude and phase)
retrieved from a perturbation vector buffer ("PVB") 167. The
perturbation vectors selected by the perturbation vector selector
165 are provided to a perturbation vector applicator ("PVA") 169
for application to the first and second antenna weighting elements
160, 162. The perturbation vectors perturb the weightings of the
first and second antenna weighting elements 160, 162 and, in turn,
the amplitude and phase of the signals transmitted by the base
station's antennas 147. The forward-channel signals generated on
the forward-link channels 105, weighted with the perturbation
vectors, are delivered to the mobile station 170.
The mobile station 170 includes a detector 190 (which may be a
subsystem of the receiver 175 and may also include a feedback
generator) that detects and measures characteristics representing
power levels of the perturbations of the forward-channel signals
(again, weighted forward-channel signals) transmitted by the base
station 100. The characteristics associated with the
forward-channel signals are thereafter transmitted by the mobile
station transmitter 180 to the base station 100. The
characteristics are thereafter employed by the base station 100 to
adjust the weightings of the first and second antenna weighting
elements 160, 162 for the base station antennas 147 to refine the
forward-channel signals.
The deterministic perturbation gradient approximation system
operates to provide a deterministic perturbation gradient
approximation that provides tracking of long-term feedback. Other
arrangements to provide feedback to adjust antenna weighting
elements are contemplated within the broad scope of the invention.
For example, U.S. Patent Application Publication No. 2007/0207730,
entitled "Adaptive Multi-Beamforming Systems and Methods for
Communication Systems," by Nguyen, et al., Sep. 6, 2007, which is
incorporated herein by reference, describe an antenna weighting
element adjustment procedure.
Turning now to FIG. 2, illustrated is a system level diagram of a
wireless communications system including a source node 205 with one
or more antennas controlled by antenna weighting factors, and a
destination node providing feedback to adjust the antenna weighting
factors. The source node 205 includes R antennas, R.gtoreq.1, such
as antenna 220, each antenna controlled with antenna weighting
factors w.sub.i, i=1, . . . , R. The wireless communication system
further includes a destination node, such as destination node 250.
The source node antennas 220 radiate through a channel 230 to an
antenna 260 at the destination node 250. In this wireless
communications system, pilot symbols or a pilot training sequence
from pilot signal source 210 at the source node 205 are transmitted
from a physical location which is the same as that where
application of antenna weighting factors takes place. An adaptive
feedback generator 270 located in destination node 250 generates a
feedback signal to adjust antenna weighting factors at a source
node 205.
There is no restriction to a particular way of adapting the antenna
weighting factors. In fact, any scheme of adapting antenna
weighting factors can be used for this purpose. The relay nodes may
or may not cooperate in knowing each others adjusted antenna
weights or (relative) transmission power and, thus, may or may not
include this cooperative knowledge in an antenna weighting factor
update procedure. Perturbations to antenna weighting factors and
the resulting control can be defined so that the adaptation method
is insensitive to the number of relay nodes, making the system
easily scalable and used.
Turning now to FIG. 3, illustrated is a system level diagram of a
wireless communication system including a source node 305, a relay
node 325 with antennas controlled by antenna weighting factors, and
a destination node 350 providing feedback to adjust the antenna
weighting factors. The source node 305 may have one or more
transmitting antennas, such as transmitting antenna 315. The
transmitting antenna(s) 315 at the source node 305 radiate through
a backward channel 320 to one or more receiving antennas, such as
receiving antenna 330 at one or more relay nodes, such as relay
node 325. The relay nodes 325 include transmitting antennas, such
as transmitting antenna 335. The transmitting antennas 335 at a
relay node 325 are controlled with R antenna weighting factors,
w.sub.i, i=1, . . . , R. Of course, a receiving antenna and a
transmitting antenna may be realized as antenna elements of a
single antenna, and when they are separate, antenna weighting
factors for receiving antennas may also be controlled. The antenna
weighting factors w.sub.i are controlled by an antenna weighting
factor module 340. The transmitting antennas 335 at a relay node
325 radiate through a forward channel 345 to a receiving antenna,
such as receiving antenna 360, at a destination node, such as
destination node 350. The source node 305 employs pilots symbols or
pilot training sequences generated in a pilot signal source 310
that are radiated from one or more source node antennas 315.
The wireless communications system applies antenna weighting factor
adjustments at one or more relay nodes that are physically separate
from a source node, determines effectiveness of the antenna
weighting factor perturbations at a destination node 350, signals
information (e.g., a feedback signal) related to effectiveness of
the perturbations via an adaptive feedback generator 370 of the
destination node 350 to the relay nodes 325, and adjusts the
antenna weighting factors by an antenna weighting factor module 340
at the relay nodes 325. At least three communication nodes are thus
employed, one of which is a relay node that has a wireless channel
to a source node and to a destination node. With a relay node, the
antenna weighting factor can enable improved signal reception, via
coherent phasing or/and power allocation, also when a direct link
exists from the source node to the destination node.
It is understood that even though the aforementioned FIGUREs show
the components of the communication nodes discussed above as
separate components, any of the components may be integrated
together or may be provided as sub-components of other components.
The functionality described above can be advantageously implemented
as software modules stored in a non-volatile memory, and executed
as needed by a processor, after copying all or part of the software
into executable random access memory. Alternatively, the logic
provided by such software can also be provided by an application
specific integrated circuit. In case of a software implementation,
the invention may be provided as a computer program product
including a computer-readable storage structure embodying computer
program code (i.e., the software therein), for execution by a
computer processor. Additionally, the dot designators in FIG. 3
represent that a communication system may include a plurality of
source, relay and destination nodes communicating therein through a
plurality of channels either directly or indirectly and possibly
through other communication nodes. For instance, an antenna of a
destination node may receive a signal from first and second
communication nodes (e.g., relay nodes) and a feedback generator
thereof may transmit a feedback signal(s), which may be different,
to one or both of the first and second communication nodes to
adjust an antenna weighting factor of an antenna thereof.
A more detailed view is now described by presenting an embodiment
of a process to adaptively adjust antenna weighting factors applied
at a relay node. As an example, a relay system with R+2
single-antenna nodes is considered wherein one source node
communicates with one destination node through a set of R
half-duplex relay nodes, as described by H. Bolcskei, et al., cited
previously hereinabove. In a first time interval, a source node
transmits a data sequence to relay nodes and, in a second time
interval, the relay nodes, after performing a linear operation on
noisy received sequences, forward a resulting signal to the
destination node. No direct communication link between the source
node and the destination node is assumed. The concept can be
extended to multiple source and destination nodes with single or
multiple antennas by use of an orthogonal multiple access scheme
(e.g., TDMA, FDMA, CDMA, etc). Moreover, the approach can also be
used with multiple-antenna relay nodes.
A transmission frame of total length N+M is defined, which includes
an estimation interval of length N time instants that is
time-multiplexed with a data sequence of length M. The estimation
interval includes a pilot training sequence transmitted from the
source node and is used to generate a feedback signal at the
destination node. After each transmission frame, the feedback
signal is used to update the antenna weighting factors at relay
nodes. Let i in the following denote the i-th antenna weighting
factor update. The actual lengths of the estimation and the data
sequences are design parameters that depend on time variation of
the backward and forward channel. Optimal choices of N and M allow
the antenna weighting factors to quickly adapt to the time-varying
nature of the channels.
The noisy pilot sequence received at each relay node is forwarded
to the destination node using two different antenna weighting
factors w+(r) and w_(r), where, r=1, . . . , R and R denotes the
r-th relay node. Specifically, certain received symbols are
dedicated to be forwarded using antenna weighting factors w+(r) and
w_(r), respectively. For convenience, the antenna weighting factors
are stacked in vectors as w+=[w+(1), . . . , w+(R)] and w_=[w_(1),
. . . , w_(R)] respectively. These antenna weighting factors are
perturbed from the tracked transmission antenna weighting factor
vector w.sub.i and can be calculated in an antenna weighting factor
module 340 as in equations (1) and (2) below using a deterministic
or random perturbation vector v as: w+=w.sub.i+.beta.v (1)
w.sub.--=w.sub.i-.beta.v (2) wherein the parameter .beta.
represents the step size of the antenna weighting factor increment,
and w.sub.i represents the antenna weight factor during the i-th
sequence of iterations.
The perturbed antenna weighting factor vectors are kept constant
during an estimation interval. Note that computation of the
perturbed antenna weighting factors can be done at each relay node
separately. The perturbation vector v may be generated from a
random Gaussian vector or from a deterministic, orthogonal vector
set. Let y+ and y_denote the received signals at the destination
node corresponding to the antenna weighting factors vectors w+ and
w_, respectively. These signals are used to generate a coarse
feedback signal. For example, the feedback signal can be computed
by estimating the received signal power P+ originating from the
antenna weighting factor w+, and the received signal power
P_originating from the antenna weighting factor w_. A one-bit
feedback signal c can then be obtained according to equation (3)
c=sign{P+-P_} (3) At the relay nodes, the feedback signal c is used
to update the antenna weighting factors in antenna weighting factor
module 340 as illustrated in equation (4):
w.sub.i+1=w.sub.i+.beta.cv (4) The step-size parameter .beta.
allows adjustment of a tradeoff between speed of adaption and
tracking accuracy. Moreover, if the relay nodes are able to
cooperate, the parameter .beta. may be a function of all antenna
weighting factors (i.e., .beta.(w(1), . . . , w(R))) to
cooperatively influence the antenna weighting factors and thus
produce a better antenna weighting factor update.
In the above description, in equation (3) the feedback signal
(e.g., a power-based feedback signal) depends on the relative
received power (or a difference thereof) obtained by the perturbed
weights. Alternative beneficial ways of determining the feedback
signal (e.g., a feedback bit) can be also constructed. For example,
the signal-to-noise based feedback signal can depend on or be a
function of the received signal-to-noise ratio or
signal-to-noise-interference ratio that is estimated using the two
perturbed weights, or any other performance measure (like resulting
throughput or capacity). Moreover, in the presence of more than one
source node (e.g., each transmitting a different pilot signal) the
destination node can compute the total (sum) SINR/throughtput at
the destination node (of any other performance metric which
converts the individual performance estimates for the two source
nodes to one value, which depends on perturbed weights) using the
two perturbed weights and find the one that gives joint
performance. This allows finding weights that enable multiplexing
of multiple source nodes, essentially so that the determined
weights (at relay nodes) eventually reduce the inference between
the simultaneously transmitted source signals when received at a
destination node (which may have more than one antenna). Here, the
different source nodes can even use different relay nodes, or
partially different relay nodes, or the same relay nodes.
As mentioned above and in addition to the power-based feedback
signal outlined in equation (3), the results herein show that a
feedback signal such as a one-bit feedback signal can also be based
on signal-to-noise based (e.g., SNR-dependent) measurements.
Generating a one-bit feedback signal based on SNR-measures yields a
significant performance gain, since it not only allows the antenna
weights to closely approach coherent combining, but also at the
same time achieves close-to-optimal power allocation of the relays
transmit powers.
As an example, it was shown by P. Larsson in a paper entitled,
"Large-scale cooperative relaying network with optimal coherent
combining under aggregate relay power constraints," in Proc. Future
Telecommunication Conference (FTC), 2003, which is incorporated
herein by reference, that in addition to coherent phase combination
of the backward and forward channels, optimal power allocation can
further improve the performance of a relay system. Optimal power
allocation ensures that those relay nodes experiencing a poor
backward and/or forward channel, transmit their noisy received
signals only with low power to prevent harmful amplification of the
dominating noise terms. Thus, the transmit power of each relay is
chosen in such a way that the received SNR at the destination node
is maximized. According to Larsson, however, optimal power
allocation requires global CSI at each relay.
Referring now to FIG. 4, illustrated is a graph demonstrating that
enhanced (e.g., optimal) power allocation can be achieved using a
learning weights method. The key to optimal power distribution lies
in SNR-dependent measurements at the destination node. Thus,
instead of determining the effectiveness of the weight
perturbations by measuring the received power at the destination
node, it is possible to measure the received SNR. Using these
SNR-dependent measurements, a one-bit feedback signal can then be
obtained similar to equation (3). This approach allows for the
convergence of coherent phase combining of the backward and forward
channel as well as the optimal power allocation simultaneously.
FIG. 4 presents bit error rate versus relay power ("P") using a
one-bit feedback weight learning scheme with SNR-dependent
measurements at the destination node with two relay nodes using an
uncoded frame with binary phase shift keying ("BPSK") modulation.
Curves are shown using a stochastic and a deterministic
perturbation set (labeled "stochastic BF" and "deterministic BF,"
respectively) for a relay system consisting of R=2 relay nodes. For
comparison, FIG. 4 illustrates the performance of optimal power
allocation with coherent combining (labeled "optimal PA," see
Larsson), coherent combining without power allocation (labeled
"coherent, no PA") and non-coherent combining without power
allocation (labeled "non-coherent, no PA"). It can be seen that the
proposed method closely attains the performance of optimal power
allocation and allows a significant performance gain as compared to
coherent combining without power allocation.
Turning now to FIG. 5, illustrated is a flow diagram demonstrating
steps that may be performed in the operation of a communication
system including a source node, one or more relay nodes with
antennas controlled by antenna weighting factors, and a destination
node providing feedback to adjust the antenna weighting factors.
The method of operating the communication system includes
generating an initial antenna weight factor w.sub.1 at a relay node
during a step 510, and transmitting a transmission frame containing
a pilot training sequence and a data sequence (e.g., a first
signal) from the source node using perturbed antenna weighting
factors at a step 520. The method continues by forwarding the
received noisy pilot sequence by the relay node to the destination
node applying the perturbed antenna weighting factors according to
equations (1) and (2) at a step 530. The method continues by
generating a feedback signal c (e.g., a second signal) at the
destination node according to received signal power using received
signals y+ and y_ corresponding to the perturbed antenna weighting
factors at a step 540. The method concludes by updating the antenna
weighting factors at the relay nodes according to equation (4) at a
step 550, and then returning to step 520 to iteratively adjust the
antenna weighting factor over a sequence of adjustment steps.
A simple experiment highlights benefits achieved by a system
constructed according to an embodiment in accordance with FIG. 6.
Consider a relay system wherein one source node communicates with
one destination node through a set of five relay nodes, all having
single antennas. Furthermore, assume single-tap Rayleigh fading
backward and forward channels, and additive, zero-mean, white
Gaussian noise at the relay nodes and at the destination node. A
transmission frame consists of an uncoded data sequence of binary
phase shift keyed ("BPSK") modulated symbols.
Referring now to FIG. 6, illustrated is a graph showing bit-error
rate ("BER") versus signal-to-noise ratio ("SNR")) expressed as the
ratio P.sub.T/N.sub.0, representing the ratio of total average
transmit power at the relay nodes to received noise power at the
destination node, in decibels ("dB"), for a one-bit deterministic
feedback antenna-weighting-factor learning scheme. The one-bit
deterministic feedback scheme is labeled "deterministic FB" in FIG.
6. The number of relay nodes is five, and an uncoded frame with
BPSK modulation is used. In this exemplary embodiment, the
perturbations applied to the antenna weighting factors at the relay
nodes were chosen from a deterministic perturbation set. The SNR of
the received signal at the relay nodes is fixed at 20 dB.
For comparison, a reference scheme (labeled "full FB") is
illustrated in FIG. 6. In this reference scheme, the backward
channel is estimated at the relay nodes transmitting dedicated
pilots from the source node, and the forward channel is estimated
at the destination node transmitting dedicated pilots from the
relay nodes. In order to compute antenna weighting factors at the
relay nodes, the full CSI of the forward channel is fed back to the
relay nodes. For a fair comparison, the total pilot overhead is set
equal for the deterministic feedback scheme and the reference full
feedback scheme. It can be seen that the performance of the
deterministic feedback scheme employing limited feedback closely
approaches the performance of the full feedback scheme in relevant
bit-error rates. It is noted that increasing the pilot overhead
would further decrease the remaining performance gap between the
two schemes.
For further comparison, extreme cases are illustrated in FIG. 6,
wherein the relay nodes have perfect CSI available in order to
calculate the antenna weighting factors (labeled "perfect CSI") and
the case wherein no CSI is available (labeled "no CSI"). In the
latter case, the received signals are noncoherently combined and,
thus, there is no or little possibility to achieve a beamforming
gain or a transmit diversity.
Turning now to FIG. 7, illustrated is convergence behavior of a
one-bit deterministic feedback scheme to adjust antenna weighting
factors with five relay nodes. The curve represents an averaged
ratio of P.sub.w/P.sub.max where P.sub.w denotes signal power at a
receiver achieved by the one-bit deterministic feedback scheme, and
P.sub.max denotes the maximum achievable signal power as a result
of ideal coherent combining The results were averaged over 500
simulation runs. It can be seen that the one-bit deterministic
feedback scheme closely approaches the maximum received power after
only a few antenna weighting factor updates.
A feedback scheme constructed according to an embodiment is
operable for any set or subset of relay node antennas, regardless
of whether the antennas belong to different relay node, to a subset
of one relay node with multiple antennas, or to any subset of
multiple relay nodes with multiple antennas. In a cooperative
wireless communication network, relay nodes can even be other
portable transceivers or terminals.
The relay nodes need not be amplify-and-forward nodes, but can be,
for instance, estimate-and-forward nodes, etc., even if
amplify-forward has been mostly assumed herein. The relay nodes may
also perform baseband operations, such as despreading and
respreading, and may perform fast Fourier transforms/inverse fast
Fourier transforms, etc., related to multiplexing of different
sources at a relay node input or output. The use of an antenna
weighting factor feedback arrangement constructed according to an
embodiment may be implemented in orthogonal frequency division
multiplexing ("OFDM")-type systems wherein node synchronization is
relaxed up to the time-span of a cyclic prefix. If the channel is
correlated in time or/and frequency, the number of pilots and the
amount of feedback can be reduced by the use of interpolation
techniques.
It is noted further that an antenna weighting factor feedback
arrangement constructed according to an embodiment is not
restricted to a specific perturbation technique, such as the one
illustrated in the example above. Moreover, perturbations can be
made in an analog domain or a digital domain. The speed of
convergence of the antenna weighting factors (e.g., the adaption
rate) and the performance of the communication system can be
increased by increasing the amount of feedback transmitted to relay
nodes. A feedback arrangement constructed according to an
embodiment may be applied for any amount of feedback. The feedback
channels defined for most wireless communication systems (e.g.,
Third Generation Partnership Program ("3GPP"), wideband code
division multiple access ("CDMA"), etc.) and similar channels can
also be used. Furthermore, pilot signals can also be multiplexed
using any conventional technique, although time division
multiplexing ("TDM") has been discussed herein for simplicity.
An antenna weighting factor feedback arrangement, constructed
according to an embodiment, employs an initialization phase at
start-up in order to produce convergence. After the initialization
phase, the antenna weighting factors produced by the feedback
arrangement are advantageously able to accurately track
time-varying channels. It is noted further that in the case of one
relay node having multiple antennas, the antenna weighting factor
feedback arrangement can be optionally modified to track a
long-term channel.
An antenna weighting factor adjustment process for a wireless
communication system including a source node, a relay node, and a
destination node has thus been described that can advantageously
adjust antenna weighting factors at the relay node for improved
reception performance at the destination node with reduced feedback
from the destination node to the relay node. An antenna weighting
factor adjustment process constructed according to an embodiment
provides decentralized antenna weighting factor updates in a
decentralized network. Conventional solutions provide antenna
weighting factor updates only in a point-to-point arrangement. A
decentralized relay network should be scalable. An increase or
decrease of the number of relay nodes in the communication system
can be accommodated in a procedure constructed according to an
embodiment with a reasonable amount of signaling overhead, and
without a major algorithm update at relay nodes. Thus, scalability
of the system is feasible and readily accommodated.
The relay nodes including an antenna weighting factor adjustment
process constructed according to an embodiment do not need CSI for
the backward or forward channel. Thus, the relay nodes do not need
to know frame pilots, etc., of the backward channel, which provides
substantial simplification of communication system design. The
relay nodes do not need explicit knowledge of the CSI of the
backward and forward channel in order to choose the optimal antenna
weights for coherent combining. Limited feedback (one-bit feedback,
in the example above) can be generated at the destination node by
transmitting pilots from the source node. The feedback enables the
antenna weighting factor adjustment process constructed according
to an embodiment to learn the correct antenna weighting factors at
the relay nodes and, thus, to coherently combine the desired signal
that is affected by both channels (e.g., the backward and the
forward channel). It should be understood that multi-bit feedback
may also be employed in a communication system with at least two
relay nodes.
If CSI is provided for the backward (or forward) channel, the
antenna weighting factor updates can still be used for the forward
(or backward) channel to accelerate convergence of the antenna
weighting factor adjustment process. Accordingly, an antenna
weighting factor update process, constructed according to an
embodiment, can be flexibly applied in a wireless communication
system. Simulation results demonstrate reasonable speed of
convergence when adapting to both backward and forward channels.
Moreover, the speed of convergence and communication performance
can be improved by increasing the amount of feedback transmitted to
the relay nodes. Also, the speed of convergence can be improved by
using CSI either at a relay node input or output. Furthermore, the
antenna weighting factor adjustment process constructed according
to an embodiment allows accurate tracking of slowly time-varying
channels. Thus, after an initialization phase in which convergence
is attained, the antenna weighting factors advantageously
adaptively follow channel variations.
As described above, the exemplary embodiment provides both a method
and corresponding apparatus consisting of various modules providing
functionality for performing the steps of the method. The modules
may be implemented as hardware (including an integrated circuit),
or may be implemented as software or firmware for execution by a
computer processor. In particular, in the case of firmware or
software, the exemplary embodiment can be provided as a computer
program product including a computer readable storage structure
embodying computer program code (i.e., software or firmware)
thereon for execution by the computer processor.
Although the present invention and its advantages have been
described in detail, it should be understood that various changes,
substitutions and alterations can be made herein without departing
from the spirit and scope of the invention as defined by the
appended claims. For example, many of the processes discussed above
can be implemented in different methodologies and replaced by other
processes, or a combination thereof, to adjust antenna weighting
factors as described herein. Moreover, the scope of the present
application is not intended to be limited to the particular
embodiments of the process, machine, manufacture, composition of
matter, means, methods and steps described in the specification. As
one of ordinary skill in the art will readily appreciate from the
disclosure of the present invention, processes, machines,
manufacture, compositions of matter, means, methods, or steps,
presently existing or later to be developed, that perform
substantially the same function or achieve substantially the same
result as the corresponding embodiments described herein may be
utilized according to the present invention. Accordingly, the
appended claims are intended to include within their scope such
processes, machines, manufacture, compositions of matter, means,
methods, or steps.
* * * * *